DatriseAI-first ETL

Zenefits to Looker Integration

AI-first ETL from Zenefits into Looker. Governed entities, incremental sync, typed landing tables.

How Datrise loads Zenefits into Looker

Datrise syncs Zenefits's employees, departments, employments, time off requests, benefits enrollments, and compensation records into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.

Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.

Ideal for governed, version-controlled BI on a warehouse.

Endpoints

Zenefits: HR, benefits, and payroll administration.

Looker: Google Cloud BI with LookML semantic models and governed dashboards.

How Zenefits entities map to Looker

Zenefits entityLooker objectNotes
employeeszenefits_employeesid PK · custom fields → flattened columns (nested fields expanded for modeling)
departmentszenefits_departmentsid PK · linked to zenefits_employees
employmentszenefits_employmentsid PK · linked to zenefits_employees
time off requestszenefits_time_off_requestsid PK · linked to zenefits_employees

FAQ

How does Datrise handle Zenefits's custom fields in Looker?

Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.

How does the Zenefits to Looker sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.

Related pipelines

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